rm(list=ls());gc()
## used (Mb) gc trigger (Mb) max used (Mb)
## Ncells 411635 22.0 851872 45.5 648454 34.7
## Vcells 756937 5.8 8388608 64.0 1699667 13.0
load("Definitive_models_2021.RData")
#xaringan::inf_mr()
#arriba puse algunas opciones para que por defecto escondiera el código
#también cargue algunos estilo .css para que el texto me apareciera justificado, entre otras cosas.
local({r <- getOption("repos")
r["CRAN"] <- "http://cran.r-project.org"
options(repos=r)
})
`%>%` <- magrittr::`%>%`
copy_names <- function(x,row.names=FALSE,col.names=TRUE,dec=",",...) {
if(class(ungroup(x))[1]=="tbl_df"){
if(options()$OutDec=="."){
options(OutDec = dec)
write.table(format(data.frame(x)),"clipboard",sep="\t",row.names=FALSE,col.names=col.names,...)
options(OutDec = ".")
return(x)
} else {
options(OutDec = ",")
write.table(format(data.frame(x)),"clipboard",sep="\t",row.names=FALSE,col.names=col.names,...)
options(OutDec = ",")
return(x)
}
} else {
if(options()$OutDec=="."){
options(OutDec = dec)
write.table(format(x),"clipboard",sep="\t",row.names=FALSE,col.names=col.names,...)
options(OutDec = ".")
return(x)
} else {
options(OutDec = ",")
write.table(format(x),"clipboard",sep="\t",row.names=FALSE,col.names=col.names,...)
options(OutDec = ",")
return(x)
}
}
}
unlink('Plots 2021-01-18_cache', recursive = TRUE)
if(!require(pacman)){install.packages("pacman")}
pacman::p_unlock(lib.loc = .libPaths()) #para no tener problemas reinstalando paquetes
knitr::opts_chunk$set(
echo = TRUE,
message = FALSE,
warning = FALSE
)
#dejo los paquetes estadÃsticos que voy a utilizar
if(!require(plotly)){install.packages("plotly")}
if(!require(lubridate)){install.packages("lubridate")}
if(!require(htmlwidgets)){install.packages("htmlwidgets")}
if(!require(tidyverse)){install.packages("tidyverse")}
if(!require(gganimate)){install.packages("gganimate")}
if(!require(readr)){install.packages("readr")}
if(!require(stringr)){install.packages("stringr")}
if(!require(data.table)){install.packages("data.table")}
if(!require(DT)){install.packages("DT")}
if(!require(ggplot2)){install.packages("ggplot2")}
if(!require(lattice)){install.packages("lattice")}
if(!require(forecast)){install.packages("forecast")}
if(!require(zoo)){install.packages("zoo")}
if(!require(panelView)){install.packages("panelView")}
if(!require(janitor)){install.packages("janitor")}
if(!require(rjson)){install.packages("rjson")}
if(!require(estimatr)){install.packages("estimatr")}
if(!require(CausalImpact)){install.packages("CausalImpact")}
if(!require(textreg)){install.packages("textreg")}
if(!require(sjPlot)){install.packages("sjPlot")}
if(!require(foreign)){install.packages("foreign")}
if(!require(tsModel)){install.packages("tsModel")}
if(!require(lmtest)){install.packages("lmtest")}
if(!require(Epi)){install.packages("Epi")}
if(!require(splines)){install.packages("splines")}
if(!require(vcd)){install.packages("vcd")}
if(!require(astsa)){install.packages("astsa")}
if(!require(forecast)){install.packages("forecast")}
if(!require(MASS)){install.packages("MASS")}
if(!require(ggsci)){install.packages("ggsci")}
if(!require(Hmisc)){install.packages("Hmisc")}
if(!require(compareGroups)){install.packages("compareGroups")}
if(!require(dplyr)){install.packages("dplyr")}
if(!require(ggforce)){install.packages("ggforce")}
if(!require(imputeTS)){install.packages("imputeTS")}
if(!require(doParallel)){install.packages("doParallel")}
if(!require(SCtools)){install.packages("SCtools")}
if(!require(MSCMT)){install.packages("MSCMT")}
# Calculate the number of cores
no_cores <- detectCores() - 1
cl<-makeCluster(no_cores)
registerDoParallel(cl)
Sys.setlocale(category = "LC_ALL", locale = "english")
## [1] "LC_COLLATE=English_United States.1252;LC_CTYPE=English_United States.1252;LC_MONETARY=English_United States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252"
library(cowplot)
#horizontal
height_y<-16
height_x<-16
size_title<-18
line_size<-1.2 #.8
Sys.setlocale(category = "LC_ALL", locale = "english")
## [1] "LC_COLLATE=English_United States.1252;LC_CTYPE=English_United States.1252;LC_MONETARY=English_United States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252"
hosp_trauma_plot_red<-
plot(impact3d_hosp_trauma, "original")$data %>%
ggplot(aes(x=time))+
geom_line(aes(y=mean), size=line_size, linetype="longdash", color="red") +
geom_line(aes(y=response), size=line_size, color="black")+
geom_ribbon(aes(ymin=lower,ymax=upper),fill="steelblue", alpha = 0.35)+
theme_sjplot()+
scale_x_continuous(breaks=(c(seq(1,nrow(data15a64_rn),24),262)),
labels=format(as.Date(unlist(data15a64_rn[c(seq(1,nrow(data15a64_rn),24),262),"date"])),"%Y %b"))+
ylim(c(0,150))+
geom_vline(xintercept = length(data15a64_rn$did[data15a64_rn$did==0]), col = "gray50", lty = 2, size=1)+
theme(axis.text.x = element_text(angle = 45, vjust = 0.5, hjust=.5,size=height_x),
# theme(axis.text.x = element_blank(),#element_text(angle = 90, vjust = 0.5, hjust=.5,size=9),
axis.text.y = element_text(size=height_y),
axis.title.y = element_blank(),
axis.title.x = element_blank(),
plot.title = element_text(size=size_title),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("c) Trauma Hospitalizations")
hosp_resp_plot_red<-
plot(impact3d1_hosp_resp, "original")$data %>%
ggplot(aes(x=time))+
geom_line(aes(y=mean), size=line_size, linetype="longdash", color="red") +
geom_line(aes(y=response), size=line_size, color="black")+
geom_ribbon(aes(ymin=lower,ymax=upper),fill="steelblue", alpha = 0.35)+
theme_sjplot()+
scale_x_continuous(breaks=(c(seq(1,nrow(data15a64_rn),24),262)),
labels=format(as.Date(unlist(data15a64_rn[c(seq(1,nrow(data15a64_rn),24),262),"date"])),"%Y %b"))+
ylim(c(0,150))+
geom_vline(xintercept = length(data15a64_rn$did[data15a64_rn$did==0]), col = "gray50", lty = 2, size=1)+
theme(axis.text.x = element_text(angle = 45, vjust = 0.5, hjust=.5,size=height_x),
# theme(axis.text.x = element_blank(),#element_text(angle = 90, vjust = 0.5, hjust=.5,size=9),
axis.text.y = element_text(size=height_y),
axis.title.y = element_blank(),
axis.title.x = element_blank(),
plot.title = element_text(size=size_title),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("d) Respiratory Hospitalizations")
cons_trauma_plot_red<-
plot(impact3d1_cons_trauma, "original")$data %>%
ggplot(aes(x=time))+
geom_line(aes(y=mean), size=line_size, linetype="longdash", color="red") +
geom_line(aes(y=response), size=line_size, color="black")+
geom_ribbon(aes(ymin=lower,ymax=upper),fill="steelblue", alpha = 0.35)+
theme_sjplot()+
scale_x_continuous(breaks=(c(seq(1,nrow(data15a64_rn),24),262)),
labels=format(as.Date(unlist(data15a64_rn[c(seq(1,nrow(data15a64_rn),24),262),"date"])),"%Y %b"))+
ylim(c(0,1600))+
geom_vline(xintercept = length(data15a64_rn$did[data15a64_rn$did==0]), col = "gray50", lty = 2, size=1)+
theme(axis.text.x = element_text(angle = 45, vjust = 0.5, hjust=.5,size=height_x),
# theme(axis.text.x = element_blank(),#element_text(angle = 90, vjust = 0.5, hjust=.5,size=9),
axis.text.y = element_text(size=height_y),
axis.title.y = element_blank(),
axis.title.x = element_blank(),
plot.title = element_text(size=size_title),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("a) Trauma Consultations")
cons_resp_plot_red<-
plot(impact3d_cons_resp, "original")$data %>%
ggplot(aes(x=time))+
geom_line(aes(y=mean), size=line_size, linetype="longdash", color="red") +
geom_line(aes(y=response), size=line_size, color="black")+
geom_ribbon(aes(ymin=lower,ymax=upper),fill="steelblue", alpha = 0.35)+
theme_sjplot()+
scale_x_continuous(breaks=(c(seq(1,nrow(data15a64_rn),24),262)),
labels=format(as.Date(unlist(data15a64_rn[c(seq(1,nrow(data15a64_rn),24),262),"date"])),"%Y %b"))+
ylim(c(0,1600))+
geom_vline(xintercept = length(data15a64_rn$did[data15a64_rn$did==0]), col = "gray50", lty = 2, size=1)+
theme(axis.text.x = element_text(angle = 45, vjust = 0.5, hjust=.5,size=height_x),
# theme(axis.text.x = element_blank(),#element_text(angle = 90, vjust = 0.5, hjust=.5,size=9),
axis.text.y = element_text(size=height_y),
axis.title.y = element_blank(),
axis.title.x = element_blank(),
plot.title = element_text(size=size_title),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("b) Respiratory Consultations")
rate_trauma_plot_red<-
plot(impact3d_cons_resp, "original")$data %>%
ggplot(aes(x=time))+
geom_line(aes(y=mean), size=line_size, linetype="longdash", color="red") +
geom_line(aes(y=response), size=line_size, color="black")+
geom_ribbon(aes(ymin=lower,ymax=upper),fill="steelblue", alpha = 0.35)+
theme_sjplot()+
scale_x_continuous(breaks=(c(seq(1,nrow(data15a64_rn),24),262)),
labels=format(as.Date(unlist(data15a64_rn[c(seq(1,nrow(data15a64_rn),24),262),"date"])),"%Y %b"))+
ylim(c(0,400))+
geom_vline(xintercept = length(data15a64_rn$did[data15a64_rn$did==0]), col = "gray50", lty = 2, size=1)+
theme(axis.text.x = element_text(angle = 45, vjust = 0.5, hjust=.5,size=height_x),
# theme(axis.text.x = element_blank(),#element_text(angle = 90, vjust = 0.5, hjust=.5,size=9),
axis.text.y = element_text(size=height_y),
axis.title.y = element_blank(),
axis.title.x = element_blank(),
plot.title = element_text(size=size_title),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("e) Trauma Hospitalizations per 1,000 consultations")
rate_resp_plot_red<-
plot(impact3d_ratio_resp, "original")$data %>%
ggplot(aes(x=time))+
geom_line(aes(y=mean), size=line_size, linetype="longdash", color="red") +
geom_line(aes(y=response), size=line_size, color="black")+
geom_ribbon(aes(ymin=lower,ymax=upper),fill="steelblue", alpha = 0.35)+
theme_sjplot()+
scale_x_continuous(breaks=(c(seq(1,nrow(data15a64_rn),24),262)),
labels=format(as.Date(unlist(data15a64_rn[c(seq(1,nrow(data15a64_rn),24),262),"date"])),"%Y %b"))+
ylim(c(0,400))+
geom_vline(xintercept = length(data15a64_rn$did[data15a64_rn$did==0]), col = "gray50", lty = 2, size=1)+
theme(axis.text.x = element_text(angle = 45, vjust = 0.5, hjust=.5,size=height_x),
# theme(axis.text.x = element_blank(),#element_text(angle = 90, vjust = 0.5, hjust=.5,size=9),
axis.text.y = element_text(size=height_y),
axis.title.y = element_blank(),
axis.title.x = element_blank(),
plot.title = element_text(size=size_title),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("f) Respiratory Hospitalizations per 1,000 consultations")
#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:
#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:
hosp_trauma_plot<-
plot(impact3d_hosp_trauma, "original")+
xlab("")+
#ylab("Hospitalizations")+
scale_x_continuous(breaks=(c(seq(1,nrow(data15a64_rn),24),262)),
labels=as.character(unlist(data15a64_rn[c(seq(1,nrow(data15a64_rn),24),262),"date"])))+
ylim(c(0,150))+
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=.5,size=height_x),
# theme(axis.text.x = element_blank(),#element_text(angle = 90, vjust = 0.5, hjust=.5,size=9),
axis.text.y = element_text(size=height_y),
axis.title.y = element_text(size=9),
axis.title.x = element_blank(),
plot.title = element_text(size=size_title),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("c) Trauma Hospitalizations")
hosp_resp_plot<-
plot(impact3d1_hosp_resp, "original")+
xlab("")+
#ylab("Hospitalizations")+
scale_x_continuous(breaks=(c(seq(1,nrow(data15a64_rn),24),262)),
labels=as.character(unlist(data15a64_rn[c(seq(1,nrow(data15a64_rn),24),262),"date"])))+
ylim(c(0,150))+
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=.5,size=height_x),
# theme(axis.text.x = element_blank(),#element_text(angle = 90, vjust = 0.5, hjust=.5,size=9),
axis.text.y = element_text(size=height_y),
axis.title.y = element_text(size=9),
axis.title.x = element_blank(),
plot.title = element_text(size=size_title),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("d) Respiratory Hospitalizations")
cons_trauma_plot<-
plot(impact3d1_cons_trauma, "original")+
xlab("")+
#ylab("Consultations")+
scale_x_continuous(breaks=(c(seq(1,nrow(data15a64_rn),24),262)),
labels=as.character(unlist(data15a64_rn[c(seq(1,nrow(data15a64_rn),24),262),"date"])))+
ylim(c(0,1600))+
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=.5,size=height_x),
# theme(axis.text.x = element_blank(),#element_text(angle = 90, vjust = 0.5, hjust=.5,size=9),
axis.text.y = element_text(size=height_y),
axis.title.y = element_text(size=9),
axis.title.x = element_blank(),
plot.title = element_text(size=size_title),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("a) Trauma Consultations")
cons_resp_plot<-
plot(impact3d_cons_resp, "original")+
xlab("")+
#ylab("Consultations")+
scale_x_continuous(breaks=(c(seq(1,nrow(data15a64_rn),24),262)),
labels=as.character(unlist(data15a64_rn[c(seq(1,nrow(data15a64_rn),24),262),"date"])))+
ylim(c(0,1600))+
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=.5,size=height_x),
# theme(axis.text.x = element_blank(),#element_text(angle = 90, vjust = 0.5, hjust=.5,size=9),
axis.text.y = element_text(size=height_y),
axis.title.y = element_text(size=9),
axis.title.x = element_blank(),
plot.title = element_text(size=size_title),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("b) Respiratory Consultations")
rate_trauma_plot<-
plot(impact3d_ratio, "original")+
xlab("")+
#ylab("Rate of Hospitalizations per Consultations")+
ylim(c(0,400))+
scale_x_continuous(breaks=(c(seq(1,nrow(data15a64_rn),24),262)),
labels=as.character(unlist(data15a64_rn[c(seq(1,nrow(data15a64_rn),24),262),"date"])))+
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=.5,size=height_x),
# theme(axis.text.x = element_blank(),#element_text(angle = 90, vjust = 0.5, hjust=.5,size=9),
axis.text.y = element_text(size=height_y),
axis.title.y = element_text(size=9),
axis.title.x = element_blank(),
plot.title = element_text(size=size_title),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("e) Trauma Hospitalizations per 1,000 consultations")
rate_resp_plot<-
plot(impact3d_ratio_resp, "original")+
xlab("")+
#ylab("Rate of Hospitalizations per Consultations")+
ylim(c(0,400))+
scale_x_continuous(breaks=(c(seq(1,nrow(data15a64_rn),24),262)),
labels=as.character(unlist(data15a64_rn[c(seq(1,nrow(data15a64_rn),24),262),"date"])))+
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=.5,size=height_x),
axis.text.y = element_text(size=height_y),
axis.title.y = element_text(size=9),
axis.title.x = element_blank(),
plot.title = element_text(size=size_title),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("f) Respiratory Hospitalizations per 1,000 consultations")
plot1<-
plot_grid(
cons_trauma_plot+theme(axis.text.x = element_blank()),
cons_resp_plot+theme(axis.text.x = element_blank()),
hosp_trauma_plot+theme(axis.text.x = element_blank()),
hosp_resp_plot+theme(axis.text.x = element_blank()),
rate_trauma_plot+theme(axis.text.x = element_blank()),
rate_resp_plot,
#get_legend(t14_trend_leg + theme(legend.position="right",
# legend.text = element_text(size = 15))),
nrow = 6, rel_heights = c(rep(1,5),1.52), align = "v"
#, rel_widths = c(1, 1)
)
#vertical
height_y<-13
height_x<-13
size_title<-14
plot1b<-
plot_grid(
cons_trauma_plot+theme(axis.text.x = element_blank()),
cons_resp_plot+theme(axis.text.x = element_blank()),
hosp_trauma_plot+theme(axis.text.x = element_blank()),
hosp_resp_plot+theme(axis.text.x = element_blank()),
rate_trauma_plot,
rate_resp_plot,#,
nrow = 3, rel_widths = c(1, 1), rel_heights = c(rep(1,3),1.7)
)
plot1b_red<-
plot_grid(
cons_trauma_plot_red+theme(axis.text.x = element_blank()),
cons_resp_plot_red+theme(axis.text.x = element_blank()),
hosp_trauma_plot_red+theme(axis.text.x = element_blank()),
hosp_resp_plot_red+theme(axis.text.x = element_blank()),
rate_trauma_plot_red,
rate_resp_plot_red,#,
nrow = 3, rel_widths = c(1, 1), rel_heights = c(rep(1,2),1.25)
)
ggdraw(plot1b_red)+
theme(plot.background = element_rect(fill=NA, color = NA))
Figure 11. Estimated Trends of the Outcomes
dont_show=1
if(dont_show==0){
pdf("_Fig1.pdf", height = 14, width = 23)
ggdraw(plot1)+
theme(plot.background = element_rect(fill=NA, color = NA))
dev.off()
}
if(dont_show==0){
jpeg("_Fig1.jpg", height = 14, width = 23, units = 'in', res = 600)
ggdraw(plot1)+
theme(plot.background = element_rect(fill=NA, color = NA))
dev.off()
}
if(dont_show==0){
pdf("_Fig1b.pdf", height = 19.5, width = 15.3)
ggdraw(plot1b)+
theme(plot.background = element_rect(fill=NA, color = NA))
dev.off()
}
if(dont_show==0){
jpeg("_Fig1b.jpg", height = 19.5, width = 15.3, units = 'in', res = 600)
ggdraw(plot1b)+
theme(plot.background = element_rect(fill=NA, color = NA))
dev.off()
}
if(dont_show==0){
pdf("_Fig1c.pdf", height = 14, width = 23)
ggdraw(plot1b_red)+
theme(plot.background = element_rect(fill=NA, color = NA))
dev.off()
}
if(dont_show==0){
jpeg("_Fig1c.jpg", height = 14, width = 23, units = 'in', res = 600)
ggdraw(plot1b_red)+
theme(plot.background = element_rect(fill=NA, color = NA))
dev.off()
}
#add_sub(, "Note. The first panel shows the data and a counterfactual prediction for the post-treatment period (Blue dashed line);\nBlue area= Prediction intervals.", vpadding=grid::unit(0, "lines"), y = .55, x = 0.03, hjust = 0,size=9)
#plot2 <- cowplot::ggdraw(grid.arrange(p14, p21,p212,p32,p42,p52,p57, ncol = 2, nrow = 4)) +
# same plot.background should be in the theme of p1 and p2 as mentioned above
# theme(plot.background = element_rect(fill=NA, color = NA))
#horizontal
height_y<-16
height_x<-16
size_title<-18
line_size<-.8
hosp_trauma_plot2_red<-
plot(impact3d_hosp_trauma, "pointwise")$data %>%
ggplot(aes(x=time))+
geom_line(aes(y=mean), size=line_size, linetype="longdash", color="darkblue") +
geom_line(aes(y=response), size=line_size, color="black")+
geom_ribbon(aes(ymin=lower,ymax=upper),fill="steelblue", alpha = 0.35)+
theme_sjplot()+
xlim(238,262)+
geom_hline(yintercept = 0, col = "black", lty = 3, size=1)+
geom_vline(xintercept = length(data15a64_rn$did[data15a64_rn$did==0]), col = "gray50", lty = 2, size=1)+
theme(axis.text.x = element_blank(),
# theme(axis.text.x = element_blank(),#element_text(angle = 90, vjust = 0.5, hjust=.5,size=9),
axis.text.y = element_text(size=height_y),
axis.title.y = element_blank(),
axis.title.x = element_blank(),
plot.title = element_text(size=size_title),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("c) Trauma Hospitalizations")
hosp_resp_plot2_red<-
plot(impact3d1_hosp_resp, "pointwise")$data %>%
ggplot(aes(x=time))+
geom_line(aes(y=mean), size=line_size, linetype="longdash", color="darkblue") +
geom_line(aes(y=response), size=line_size, color="black")+
geom_ribbon(aes(ymin=lower,ymax=upper),fill="steelblue", alpha = 0.35)+
theme_sjplot()+
xlim(238,262)+
geom_hline(yintercept = 0, col = "black", lty = 3, size=1)+
geom_vline(xintercept = length(data15a64_rn$did[data15a64_rn$did==0]), col = "gray50", lty = 2, size=1)+
theme(axis.text.x = element_blank(),
# theme(axis.text.x = element_blank(),#element_text(angle = 90, vjust = 0.5, hjust=.5,size=9),
axis.text.y = element_text(size=height_y),
axis.title.y = element_blank(),
axis.title.x = element_blank(),
plot.title = element_text(size=size_title),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("d) Respiratory Hospitalizations")
cons_trauma_plot2_red<-
plot(impact3d1_cons_trauma, "pointwise")$data %>%
ggplot(aes(x=time))+
geom_line(aes(y=mean), size=line_size, linetype="longdash", color="darkblue") +
geom_line(aes(y=response), size=line_size, color="black")+
geom_ribbon(aes(ymin=lower,ymax=upper),fill="steelblue", alpha = 0.35)+
theme_sjplot()+
xlim(238,262)+
geom_hline(yintercept = 0, col = "black", lty = 3, size=1)+
geom_vline(xintercept = length(data15a64_rn$did[data15a64_rn$did==0]), col = "gray50", lty = 2, size=1)+
theme(axis.text.x = element_blank(),
# theme(axis.text.x = element_blank(),#element_text(angle = 90, vjust = 0.5, hjust=.5,size=9),
axis.text.y = element_text(size=height_y),
axis.title.y = element_blank(),
axis.title.x = element_blank(),
plot.title = element_text(size=size_title),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("a) Trauma Consultations")
cons_resp_plot2_red<-
plot(impact3d_cons_resp, "pointwise")$data %>%
ggplot(aes(x=time))+
geom_line(aes(y=mean), size=line_size, linetype="longdash", color="darkblue") +
geom_line(aes(y=response), size=line_size, color="black")+
geom_ribbon(aes(ymin=lower,ymax=upper),fill="steelblue", alpha = 0.35)+
theme_sjplot()+
xlim(238,262)+
geom_hline(yintercept = 0, col = "black", lty = 3, size=1)+
geom_vline(xintercept = length(data15a64_rn$did[data15a64_rn$did==0]), col = "gray50", lty = 2, size=1)+
theme(axis.text.x = element_blank(),
# theme(axis.text.x = element_blank(),#element_text(angle = 90, vjust = 0.5, hjust=.5,size=9),
axis.text.y = element_text(size=height_y),
axis.title.y = element_blank(),
axis.title.x = element_blank(),
plot.title = element_text(size=size_title),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("b) Respiratory Consultations")
rate_trauma_plot2_red<-
plot(impact3d_ratio, "pointwise")$data %>%
ggplot(aes(x=time))+
geom_line(aes(y=mean), size=line_size, linetype="longdash", color="darkblue") +
geom_line(aes(y=response), size=line_size, color="black")+
geom_ribbon(aes(ymin=lower,ymax=upper),fill="steelblue", alpha = 0.35)+
theme_sjplot()+
xlim(238,262)+
geom_hline(yintercept = 0, col = "black", lty = 3, size=1)+
geom_vline(xintercept = length(data15a64_rn$did[data15a64_rn$did==0]), col = "gray50", lty = 2, size=1)+
theme(axis.text.x = element_text(angle = 45, vjust = 0.5, hjust=.5,size=height_x),
# theme(axis.text.x = element_blank(),#element_text(angle = 90, vjust = 0.5, hjust=.5,size=9),
axis.text.y = element_text(size=height_y),
axis.title.y = element_blank(),
axis.title.x = element_blank(),
plot.title = element_text(size=size_title),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("e) Trauma Hospitalizations per 1,000 consultations")
rate_resp_plot2_red<-
plot(impact3d_ratio_resp, "pointwise")$data %>%
ggplot(aes(x=time))+
geom_line(aes(y=mean), size=line_size, linetype="longdash", color="darkblue") +
geom_line(aes(y=response), size=line_size, color="black")+
geom_ribbon(aes(ymin=lower,ymax=upper),fill="steelblue", alpha = 0.35)+
theme_sjplot()+
xlim(238,262)+
geom_hline(yintercept = 0, col = "black", lty = 3, size=1)+
geom_vline(xintercept = length(data15a64_rn$did[data15a64_rn$did==0]), col = "gray50", lty = 2, size=1)+
theme(axis.text.x = element_text(angle = 45, vjust = 0.5, hjust=.5,size=height_x),
# theme(axis.text.x = element_blank(),#element_text(angle = 90, vjust = 0.5, hjust=.5,size=9),
axis.text.y = element_text(size=height_y),
axis.title.y = element_blank(),
axis.title.x = element_blank(),
plot.title = element_text(size=size_title),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("f) Respiratory Hospitalizations per 1,000 consultations")
vector_breaks_plot2b_red<- seq(238,nrow(data15a64_rn),3)
Sys.setlocale(category = "LC_ALL", locale = "english")
## [1] "LC_COLLATE=English_United States.1252;LC_CTYPE=English_United States.1252;LC_MONETARY=English_United States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252"
vector_dates_plot2b_red<-as.character(format(as.Date(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),"%b %d"))
plot2b_red<-
plot_grid(
cons_trauma_plot2_red+scale_x_continuous(breaks=vector_breaks_plot2b_red,labels=vector_dates_plot2b_red,limits=c(238,262))+scale_y_continuous(breaks=seq(-800,300,200), limits = c(-800,300)),
cons_resp_plot2_red+scale_x_continuous(breaks=vector_breaks_plot2b_red,labels=vector_dates_plot2b_red,limits=c(238,262))+scale_y_continuous(breaks=seq(-800,300,200), limits = c(-800,300)),
hosp_trauma_plot2_red+scale_x_continuous(breaks=vector_breaks_plot2b_red,labels=vector_dates_plot2b_red,limits=c(238,262))+scale_y_continuous(breaks=seq(-75,75,25), limits = c(-75,75)),
hosp_resp_plot2_red+scale_x_continuous(breaks=vector_breaks_plot2b_red,labels=vector_dates_plot2b_red,limits=c(238,262))+scale_y_continuous(breaks=seq(-75,75,25), limits = c(-75,75)),
rate_trauma_plot2_red+scale_x_continuous(breaks=vector_breaks_plot2b_red,labels=vector_dates_plot2b_red,limits=c(238,262))+scale_y_continuous(breaks=seq(-400,400,200), limits = c(-400,400)),
rate_resp_plot2_red+scale_x_continuous(breaks=vector_breaks_plot2b_red,labels=vector_dates_plot2b_red,limits=c(238,262))+scale_y_continuous(breaks=seq(-400,400,200), limits = c(-400,400)),
#get_legend(t14_trend_leg + theme(legend.position="right",
# legend.text = element_text(size = 15))),
nrow = 3, rel_widths = c(.95, .95), rel_heights = c(rep(1,2),1.3), scale = c(.95, .95, .95,.95,.95,.95)
)+
draw_label("Weekly difference change in consultations/hospitalizations",x=0.005, y=.5, angle=90, size = 17)
#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:
#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:
#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:
#vertical
height_y<-13
height_x<-13
size_title<-14
hosp_trauma_plot2<-
plot(impact3d_hosp_trauma, "pointwise")+
xlab("")+
#ylab("Hospitalizations")+
xlim(238,262)+
theme(axis.text.x = element_text(angle = 45, vjust = 0.5, hjust=.5,size=height_x),
axis.text.y = element_text(size=height_y),
axis.title.y = element_text(size=9),
axis.title.x = element_blank(),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("c) Trauma Hospitalizations")+
theme(plot.title = element_text(size=size_title))
hosp_resp_plot2<-
plot(impact3d1_hosp_resp, "pointwise")+
xlab("")+
#ylab("Hospitalizations")+
xlim(238,262)+
theme(axis.text.x = element_text(angle = 45, vjust = 0.5, hjust=.5,size=height_x),
axis.text.y = element_text(size=height_y),
axis.title.y = element_text(size=9),
axis.title.x = element_blank(),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("d) Respiratory Hospitalizations")+
theme(plot.title = element_text(size=size_title))
cons_trauma_plot2<-
plot(impact3d1_cons_trauma, "pointwise")+
xlab("")+
#ylab("Consultations")+
xlim(238,262)+
theme(axis.text.x = element_text(angle = 45, vjust = 0.5, hjust=.5,size=height_x),
axis.text.y = element_text(size=height_y),
axis.title.y = element_text(size=9),
axis.title.x = element_blank(),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("a) Trauma Consultations")+
theme(plot.title = element_text(size=size_title))
cons_resp_plot2<-
plot(impact3d_cons_resp, "pointwise")+
xlab("")+
#ylab("Consultations")+
xlim(238,262)+
theme(axis.text.x = element_text(angle = 45, vjust = 0.5, hjust=.5,size=height_x),
axis.text.y = element_text(size=height_y),
axis.title.y = element_text(size=9),
axis.title.x = element_blank(),
plot.caption = element_text(hjust = 0, face= "italic",size=12))+
ggtitle("b) Respiratory Consultations")+
theme(plot.title = element_text(size=size_title))
rate_trauma_plot2<-
plot(impact3d_ratio, "pointwise")+
xlab("")+
#ylab("Rate of Hospitalizations per Consultations")+
xlim(238,262)+
theme(axis.text.x = element_text(angle = 45, vjust = 0.5, hjust=.5,size=height_x),
axis.text.y = element_text(size=height_y),
axis.title.y = element_text(size=9),
axis.title.x = element_blank(),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("e) Trauma Hospitalizations per 1,000 consultations")+
theme(plot.title = element_text(size=size_title))
rate_resp_plot2<-
plot(impact3d_ratio_resp, "pointwise")+
xlab("")+
#ylab("Rate of Hospitalizations per Consultations")+
xlim(238,262)+
theme(axis.text.x = element_text(angle = 45, vjust = 0.5, hjust=.5,size=height_x),
axis.text.y = element_text(size=height_y),
axis.title.y = element_text(size=9),
axis.title.x = element_blank(),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("f) Respiratory Hospitalizations per 1,000 consultations")+
theme(plot.title = element_text(size=size_title))
Sys.setlocale(category = "LC_ALL", locale = "english")
## [1] "LC_COLLATE=English_United States.1252;LC_CTYPE=English_United States.1252;LC_MONETARY=English_United States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252"
plot2<-
plot_grid(
cons_trauma_plot2+scale_x_continuous(breaks=seq(238,nrow(data15a64_rn),3),labels=format(as.Date(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),"%b %d"),limits=c(238,262))+scale_y_continuous(breaks=seq(-800,300,200), limits = c(-800,300)),
cons_resp_plot2+scale_x_continuous(breaks=seq(238,nrow(data15a64_rn),3),labels=format(as.Date(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),"%b %d"),limits=c(238,262))+scale_y_continuous(breaks=seq(-800,300,200), limits = c(-800,300)),
hosp_trauma_plot2+scale_x_continuous(breaks=seq(238,nrow(data15a64_rn),3),labels=format(as.Date(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),"%b %d"),limits=c(238,262))+scale_y_continuous(breaks=seq(-75,75,25), limits = c(-75,75)),
hosp_resp_plot2+scale_x_continuous(breaks=seq(238,nrow(data15a64_rn),3),labels=format(as.Date(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),"%b %d"),limits=c(238,262))+scale_y_continuous(breaks=seq(-75,75,25), limits = c(-75,75)),
rate_trauma_plot2+scale_x_continuous(breaks=seq(238,nrow(data15a64_rn),3),labels=format(as.Date(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),"%b %d"),limits=c(238,262))+scale_y_continuous(breaks=seq(-100,400,100), limits = c(-100,400)),
rate_resp_plot2+scale_x_continuous(breaks=seq(238,nrow(data15a64_rn),3),labels=format(as.Date(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),"%b %d"),limits=c(238,262))+scale_y_continuous(breaks=seq(-100,400,100), limits = c(-100,400)),
#get_legend(t14_trend_leg + theme(legend.position="right",
# legend.text = element_text(size = 15))),
nrow = 3, rel_widths = c(1, 1)
)+
draw_label("Weekly difference change in consultations/hospitalizations",x=0.01, y=.5, angle=90, size = 14)
#horizontal
height_y<-15
height_x<-15
size_title<-16
Sys.setlocale(category = "LC_ALL", locale = "english")
## [1] "LC_COLLATE=English_United States.1252;LC_CTYPE=English_United States.1252;LC_MONETARY=English_United States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252"
plot2b<-
plot_grid(
cons_trauma_plot2+scale_x_continuous(breaks=seq(238,nrow(data15a64_rn),3),labels=format(as.Date(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),"%b %d"),limits=c(238,262))+scale_y_continuous(breaks=seq(-800,300,200), limits = c(-800,300)),
cons_resp_plot2+scale_x_continuous(breaks=seq(238,nrow(data15a64_rn),3),labels=format(as.Date(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),"%b %d"),limits=c(238,262))+scale_y_continuous(breaks=seq(-800,300,200), limits = c(-800,300)),
hosp_trauma_plot2+scale_x_continuous(breaks=seq(238,nrow(data15a64_rn),3),labels=format(as.Date(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),"%b %d"),limits=c(238,262))+scale_y_continuous(breaks=seq(-75,75,25), limits = c(-75,75)),
hosp_resp_plot2+scale_x_continuous(breaks=seq(238,nrow(data15a64_rn),3),labels=format(as.Date(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),"%b %d"),limits=c(238,262))+scale_y_continuous(breaks=seq(-75,75,25), limits = c(-75,75)),
rate_trauma_plot2+scale_x_continuous(breaks=seq(238,nrow(data15a64_rn),3),labels=format(as.Date(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),"%b %d"),limits=c(238,262))+scale_y_continuous(breaks=seq(-100,400,100), limits = c(-100,400)),
rate_resp_plot2+scale_x_continuous(breaks=seq(238,nrow(data15a64_rn),3),labels=format(as.Date(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),"%b %d"),limits=c(238,262))+scale_y_continuous(breaks=seq(-100,400,100), limits = c(-100,400)),
#get_legend(t14_trend_leg + theme(legend.position="right",
# legend.text = element_text(size = 15))),
nrow = 3, rel_widths = c(1, 1)
)+
draw_label("Weekly difference change in consultations/hospitalizations",x=0.01, y=.5, angle=90, size = 14)
#draw_figure_label(label = "\n\nFigure 1", angle = -90, colour = "black", position="bottom.left", size=20)
ggdraw(plot2b_red)+
theme(plot.background = element_rect(fill=NA, color = NA))
Figure 12. Estimated Trends of the Outcomes
#add_sub(, "Note. Difference between observed data and counterfactual predictions;\nBlue area= Prediction intervals.",
#vpadding=grid::unit(0, "lines"),
# y = .55, x = 0.03, hjust = 0,size=9)
if(dont_show==0){
pdf("___Fig2.pdf", width = 15.3, height = 19.5)
ggdraw(plot2)+
theme(plot.background = element_rect(fill=NA, color = NA))
dev.off()
}
if(dont_show==0){
jpeg("_Fig2.jpg", width = 15.3, height = 19.5, units = 'in', res = 600)
ggdraw(plot2)+
theme(plot.background = element_rect(fill=NA, color = NA))
dev.off()
}
if(dont_show==0){
pdf("_Fig2b.pdf", height = 14, width = 23)
ggdraw(plot2b)+
theme(plot.background = element_rect(fill=NA, color = NA))
dev.off()
}
if(dont_show==0){
jpeg("_Fig2b.jpg", height = 14, width = 23, units = 'in', res = 600)
ggdraw(plot2b)+
theme(plot.background = element_rect(fill=NA, color = NA))
dev.off()
}
if(dont_show==0){
pdf("_Fig2c.pdf", height = 14, width = 23)
ggdraw(plot2b_red)+
theme(plot.background = element_rect(fill=NA, color = NA))
dev.off()
}
if(dont_show==0){
jpeg("_Fig2c.jpg", height = 14, width = 23, units = 'in', res = 600)
ggdraw(plot2b_red)+
theme(plot.background = element_rect(fill=NA, color = NA))
dev.off()
}
#horizontal
height_y<-16
height_x<-16
size_title<-18
line_size<-.8
hosp_trauma_plot3_red<-
plot(impact3d_hosp_trauma, "cumulative")$data %>%
ggplot(aes(x=time))+
geom_line(aes(y=mean), size=line_size, linetype="longdash", color="darkblue") +
geom_line(aes(y=response), size=line_size, color="black")+
geom_ribbon(aes(ymin=lower,ymax=upper),fill="steelblue", alpha = 0.35)+
theme_sjplot()+
xlim(238,262)+
geom_hline(yintercept = 0, col = "black", lty = 3, size=1)+
geom_vline(xintercept = length(data15a64_rn$did[data15a64_rn$did==0]), col = "gray50", lty = 2, size=1)+
theme(axis.text.x = element_blank(),
# theme(axis.text.x = element_blank(),#element_text(angle = 90, vjust = 0.5, hjust=.5,size=9),
axis.text.y = element_text(size=height_y),
axis.title.y = element_blank(),
axis.title.x = element_blank(),
plot.title = element_text(size=size_title),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("c) Trauma Hospitalizations")
hosp_resp_plot3_red<-
plot(impact3d1_hosp_resp, "cumulative")$data %>%
ggplot(aes(x=time))+
geom_line(aes(y=mean), size=line_size, linetype="longdash", color="darkblue") +
geom_line(aes(y=response), size=line_size, color="black")+
geom_ribbon(aes(ymin=lower,ymax=upper),fill="steelblue", alpha = 0.35)+
theme_sjplot()+
xlim(238,262)+
geom_hline(yintercept = 0, col = "black", lty = 3, size=1)+
geom_vline(xintercept = length(data15a64_rn$did[data15a64_rn$did==0]), col = "gray50", lty = 2, size=1)+
theme(axis.text.x = element_blank(),
# theme(axis.text.x = element_blank(),#element_text(angle = 90, vjust = 0.5, hjust=.5,size=9),
axis.text.y = element_text(size=height_y),
axis.title.y = element_blank(),
axis.title.x = element_blank(),
plot.title = element_text(size=size_title),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("d) Respiratory Hospitalizations")
cons_trauma_plot3_red<-
plot(impact3d1_cons_trauma, "cumulative")$data %>%
ggplot(aes(x=time))+
geom_line(aes(y=mean), size=line_size, linetype="longdash", color="darkblue") +
geom_line(aes(y=response), size=line_size, color="black")+
geom_ribbon(aes(ymin=lower,ymax=upper),fill="steelblue", alpha = 0.35)+
theme_sjplot()+
xlim(238,262)+
geom_hline(yintercept = 0, col = "black", lty = 3, size=1)+
geom_vline(xintercept = length(data15a64_rn$did[data15a64_rn$did==0]), col = "gray50", lty = 2, size=1)+
theme(axis.text.x = element_blank(),
# theme(axis.text.x = element_blank(),#element_text(angle = 90, vjust = 0.5, hjust=.5,size=9),
axis.text.y = element_text(size=height_y),
axis.title.y = element_blank(),
axis.title.x = element_blank(),
plot.title = element_text(size=size_title),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("a) Trauma Consultations")
cons_resp_plot3_red<-
plot(impact3d_cons_resp, "cumulative")$data %>%
ggplot(aes(x=time))+
geom_line(aes(y=mean), size=line_size, linetype="longdash", color="darkblue") +
geom_line(aes(y=response), size=line_size, color="black")+
geom_ribbon(aes(ymin=lower,ymax=upper),fill="steelblue", alpha = 0.35)+
theme_sjplot()+
xlim(238,262)+
geom_hline(yintercept = 0, col = "black", lty = 3, size=1)+
geom_vline(xintercept = length(data15a64_rn$did[data15a64_rn$did==0]), col = "gray50", lty = 2, size=1)+
theme(axis.text.x = element_blank(),
# theme(axis.text.x = element_blank(),#element_text(angle = 90, vjust = 0.5, hjust=.5,size=9),
axis.text.y = element_text(size=height_y),
axis.title.y = element_blank(),
axis.title.x = element_blank(),
plot.title = element_text(size=size_title),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("b) Respiratory Consultations")
rate_trauma_plot3_red<-
plot(impact3d_ratio, "cumulative")$data %>%
ggplot(aes(x=time))+
geom_line(aes(y=mean), size=line_size, linetype="longdash", color="darkblue") +
geom_line(aes(y=response), size=line_size, color="black")+
geom_ribbon(aes(ymin=lower,ymax=upper),fill="steelblue", alpha = 0.35)+
theme_sjplot()+
xlim(238,262)+
geom_hline(yintercept = 0, col = "black", lty = 3, size=1)+
geom_vline(xintercept = length(data15a64_rn$did[data15a64_rn$did==0]), col = "gray50", lty = 2, size=1)+
theme(axis.text.x = element_text(angle = 45, vjust = 0.5, hjust=.5,size=height_x),
# theme(axis.text.x = element_blank(),#element_text(angle = 90, vjust = 0.5, hjust=.5,size=9),
axis.text.y = element_text(size=height_y),
axis.title.y = element_blank(),
axis.title.x = element_blank(),
plot.title = element_text(size=size_title),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("e) Trauma Hospitalizations per 1,000 consultations")
rate_resp_plot3_red<-
plot(impact3d_ratio_resp, "cumulative")$data %>%
ggplot(aes(x=time))+
geom_line(aes(y=mean), size=line_size, linetype="longdash", color="darkblue") +
geom_line(aes(y=response), size=line_size, color="black")+
geom_ribbon(aes(ymin=lower,ymax=upper),fill="steelblue", alpha = 0.35)+
theme_sjplot()+
xlim(238,262)+
geom_hline(yintercept = 0, col = "black", lty = 3, size=1)+
geom_vline(xintercept = length(data15a64_rn$did[data15a64_rn$did==0]), col = "gray50", lty = 2, size=1)+
theme(axis.text.x = element_text(angle = 45, vjust = 0.5, hjust=.5,size=height_x),
# theme(axis.text.x = element_blank(),#element_text(angle = 90, vjust = 0.5, hjust=.5,size=9),
axis.text.y = element_text(size=height_y),
axis.title.y = element_blank(),
axis.title.x = element_blank(),
plot.title = element_text(size=size_title),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("f) Respiratory Hospitalizations per 1,000 consultations")
vector_breaks_plot3b_red<- seq(238,nrow(data15a64_rn),3)
Sys.setlocale(category = "LC_ALL", locale = "english")
## [1] "LC_COLLATE=English_United States.1252;LC_CTYPE=English_United States.1252;LC_MONETARY=English_United States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252"
vector_dates_plot3b_red<-as.character(format(as.Date(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),"%b %d"))
plot3b_red<-
plot_grid(
cons_trauma_plot3_red+scale_x_continuous(breaks=vector_breaks_plot3b_red,labels=vector_dates_plot3b_red,limits=c(238,262))+scale_y_continuous(breaks=seq(-5000,2000,1000), limits = c(-5000,2000)),
cons_resp_plot3_red+scale_x_continuous(breaks=vector_breaks_plot3b_red,labels=vector_dates_plot3b_red,limits=c(238,262))+scale_y_continuous(breaks=seq(-5000,2000,1000), limits = c(-5000,2000)),
hosp_trauma_plot3_red+scale_x_continuous(breaks=vector_breaks_plot3b_red,labels=vector_dates_plot3b_red,limits=c(238,262))+scale_y_continuous(breaks=seq(-250,250,100), limits = c(-250,250)),
hosp_resp_plot3_red+scale_x_continuous(breaks=vector_breaks_plot3b_red,labels=vector_dates_plot3b_red,limits=c(238,262))+scale_y_continuous(breaks=seq(-250,250,100), limits = c(-250,250)),
rate_trauma_plot3_red+scale_x_continuous(breaks=vector_breaks_plot3b_red,labels=vector_dates_plot3b_red,limits=c(238,262))+scale_y_continuous(breaks=seq(-100,1500,250), limits = c(-100,1500)),
rate_resp_plot3_red+scale_x_continuous(breaks=vector_breaks_plot3b_red,labels=vector_dates_plot3b_red,limits=c(238,262))+scale_y_continuous(breaks=seq(-100,1500,250), limits = c(-100,1500)),
#get_legend(t14_trend_leg + theme(legend.position="right",
# legend.text = element_text(size = 15))),
nrow = 3, rel_widths = c(1, 1), rel_heights = c(rep(1,2),1.25), scale = c(.95, .95, .95,.95,.95,.95))+
draw_label("Weekly difference change in consultations/hospitalizations",x=0.005, y=.5, angle=90, size = 17)
#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:#:
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#
#vertical
height_y<-13
height_x<-13
size_title<-14
#horizontal
hosp_trauma_plot3<-
plot(impact3d_hosp_trauma, "cumulative")+
xlab("")+
# ylab("Hospitalizations")+
xlim(238,262)+
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=.5,size=height_x),
axis.text.y = element_text(size=height_y),
axis.title.y = element_text(size=9),
axis.title.x = element_blank(),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("c) Trauma Hospitalizations")+
theme(plot.title = element_text(size=size_title))
hosp_resp_plot3<-
plot(impact3d1_hosp_resp, "cumulative")+
xlab("")+
# ylab("Hospitalizations")+
xlim(238,262)+
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=.5,size=height_x),
axis.text.y = element_text(size=height_y),
axis.title.y = element_text(size=9),
axis.title.x = element_blank(),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("d) Respiratory Hospitalizations")+
theme(plot.title = element_text(size=size_title))
cons_trauma_plot3<-
plot(impact3d1_cons_trauma, "cumulative")+
xlab("")+
# ylab("Consultations")+
xlim(238,262)+
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=.5,size=height_x),
axis.text.y = element_text(size=height_y),
axis.title.y = element_text(size=9),
axis.title.x = element_blank(),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("a) Trauma Consultations")+
theme(plot.title = element_text(size=size_title))
cons_resp_plot3<-
plot(impact3d_cons_resp, "cumulative")+
xlab("")+
# ylab("Consultations")+
xlim(238,262)+
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=.5,size=height_x),
axis.text.y = element_text(size=height_y),
axis.title.y = element_text(size=9),
axis.title.x = element_blank(),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("b) Respiratory Consultations")+
theme(plot.title = element_text(size=size_title))
rate_trauma_plot3<-
plot(impact3d_ratio, "cumulative")+
xlab("")+
# ylab("Rate of Hospitalizations per Consultations")+
xlim(238,262)+
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=.5,size=height_x),
axis.text.y = element_text(size=height_y),
axis.title.y = element_text(size=9),
axis.title.x = element_blank(),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("e) Trauma Hospitalizations per 1,000 consultations")+
theme(plot.title = element_text(size=size_title))
rate_resp_plot3<-
plot(impact3d_ratio_resp, "cumulative")+
xlab("")+
# ylab("Rate of Hospitalizations per Consultations")+
xlim(238,262)+
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=.5,size=height_x),
axis.text.y = element_text(size=height_y),
axis.title.y = element_text(size=9),
axis.title.x = element_blank(),
plot.caption = element_text(hjust = 0, face= "italic",size=9))+
ggtitle("f) Respiratory Hospitalizations per 1,000 consultations")+
theme(plot.title = element_text(size=size_title))
plot3<-
plot_grid(
cons_trauma_plot3+scale_x_continuous(breaks=seq(238,nrow(data15a64_rn),3),labels=as.character(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),limits=c(238,262))+scale_y_continuous(breaks=seq(-4000,2000,1000), limits = c(-4000,2000)),
cons_resp_plot3+scale_x_continuous(breaks=seq(238,nrow(data15a64_rn),3),labels=as.character(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),limits=c(238,262))+scale_y_continuous(breaks=seq(-4000,2000,1000), limits = c(-4000,2000)),
hosp_trauma_plot3+scale_x_continuous(breaks=seq(238,nrow(data15a64_rn),3),labels=as.character(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),limits=c(238,262))+scale_y_continuous(breaks=seq(-250,250,100), limits = c(-250,250)),
hosp_resp_plot3+scale_x_continuous(breaks=seq(238,nrow(data15a64_rn),3),labels=as.character(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),limits=c(238,262))+scale_y_continuous(breaks=seq(-250,250,100), limits = c(-250,250)),
rate_trauma_plot3+scale_x_continuous(breaks=seq(238,nrow(data15a64_rn),3),labels=as.character(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),limits=c(238,262))+scale_y_continuous(breaks=seq(-100,1500,250), limits = c(-100,1500)),
rate_resp_plot3+scale_x_continuous(breaks=seq(238,nrow(data15a64_rn),3),labels=as.character(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),limits=c(238,262))+scale_y_continuous(breaks=seq(-100,1500,250), limits = c(-100,1500)),#,
#get_legend(t14_trend_leg + theme(legend.position="right",
# legend.text = element_text(size = 15))),
nrow = 3, rel_widths = c(1, 1)
)
height_y<-15
height_x<-15
size_title<-16
plot3b<-
plot_grid(
cons_trauma_plot3+scale_x_continuous(breaks=seq(238,nrow(data15a64_rn),3),labels=as.character(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),limits=c(238,262))+scale_y_continuous(breaks=seq(-4000,2000,1000), limits = c(-4000,2000)),
cons_resp_plot3+scale_x_continuous(breaks=seq(238,nrow(data15a64_rn),3),labels=as.character(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),limits=c(238,262))+scale_y_continuous(breaks=seq(-4000,2000,1000), limits = c(-4000,2000)),
hosp_trauma_plot3+scale_x_continuous(breaks=seq(238,nrow(data15a64_rn),3),labels=as.character(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),limits=c(238,262))+scale_y_continuous(breaks=seq(-250,250,100), limits = c(-250,250)),
hosp_resp_plot3+scale_x_continuous(breaks=seq(238,nrow(data15a64_rn),3),labels=as.character(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),limits=c(238,262))+scale_y_continuous(breaks=seq(-250,250,100), limits = c(-250,250)),
rate_trauma_plot3+scale_x_continuous(breaks=seq(238,nrow(data15a64_rn),3),labels=as.character(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),limits=c(238,262))+scale_y_continuous(breaks=seq(-100,1500,250), limits = c(-100,1500)),
rate_resp_plot3+scale_x_continuous(breaks=seq(238,nrow(data15a64_rn),3),labels=as.character(unlist(data15a64_rn[c(seq(238,nrow(data15a64_rn),3)),"date"])),limits=c(238,262))+scale_y_continuous(breaks=seq(-100,1500,250), limits = c(-100,1500)),#,
#get_legend(t14_trend_leg + theme(legend.position="right",
# legend.text = element_text(size = 15))),
nrow = 3, rel_widths = c(1, 1)
)
#add_sub(, "Note. Added pointwise contributions from the second panel;\nBlue area= Cumulative intervals;\nBlue area= Prediction intervals.",
#vpadding=grid::unit(0, "lines"),
# y = .55, x = 0.03, hjust = 0,size=9))+
ggdraw(plot3b_red)+
theme(plot.background = element_rect(fill=NA, color = NA))
Figure 13. Estimated Trends of the Outcomes
if(dont_show==0){
pdf("___Fig3.pdf", width = 15.3, height = 19.5)
ggdraw(plot3)+
theme(plot.background = element_rect(fill=NA, color = NA))
dev.off()
}
if(dont_show==0){
jpeg("_Fig3.jpg", width = 15.3, height = 19.5, units = 'in', res = 600)
ggdraw(plot3)+
theme(plot.background = element_rect(fill=NA, color = NA))
dev.off()
}
if(dont_show==0){
pdf("_Fig3b.pdf", height = 14, width = 23)
ggdraw(plot3b)+
theme(plot.background = element_rect(fill=NA, color = NA))
dev.off()
}
if(dont_show==0){
jpeg("_Fig3b.jpg", height = 14, width = 23, units = 'in', res = 600)
ggdraw(plot3b)+
theme(plot.background = element_rect(fill=NA, color = NA))
dev.off()
}
if(dont_show==0){
pdf("_Fig3c.pdf", height = 14, width = 23)
ggdraw(plot3b_red)+
theme(plot.background = element_rect(fill=NA, color = NA))
dev.off()
}
if(dont_show==0){
jpeg("_Fig3c.jpg", height = 14, width = 23, units = 'in', res = 600)
ggdraw(plot3b_red)+
theme(plot.background = element_rect(fill=NA, color = NA))
dev.off()
}